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The cataluminescence (CTL) reaction detects the presence and concentration of toxic volatile organic compounds by detecting the luminescence intensity of the different components of the gas mixture. In our study, a cataluminescence online sensor system based on LaCO 3 OH microspheres was developed for the low concentration detection of volatile organic compounds. Multi-dimensional CTL test was carried out to analyse the correlation characteristics of heterogeneous analytes among the catalytic activity, selectivity, sensitivity, response/recover time, stability, and photoelectric signals by changing the parameters of wavelength, flow rate, temperature, and response time under the optimal conditions (280 mL/min, 180ºC, and 480 nm). Due to noise interference received by the CTL signal, the weak CTL signal was filtered based on the time-frequency characteristics of the CTL pattern signal power frequency interference and background noise. Next, this study also studied the mechanism action of the cataluminescence sensor based on LaCO 3 OH microspheres for gas detection, including ethyl ether, acetone, chloroform, and formaldehyde. The principal component analysis (PCA) algorithm was adopted to analyse the CTL patterns, after threshold filtering, the total variance was improved from 89.23% to 98.78% and each vapour gave its unique CTL patterns. Moreover, clustering and identification are discussed to analyse the results, including Hierarchical Cluster Analysis (HCA) and Radial Basis Function Neural Networks (RBFNN), was also discussed. The excellent cluster and recognition ability indicate the feasibility of this CTL sensor for volatile compound determination. • A LaCO 3 OH-microspheres-based cataluminescence sensor was developed for the detection of VOCs firstly. • Multi-dimensional analytes test was carried out among the catalytic activity, selectivity, sensitivity, response/recover time, stability, and photoelectric signals. • Studied the mechanism action of the cataluminescence sensor based on LaCO 3 OH microspheres for gas detection. • The total variance of PCA increased from 89.23% to 98.78% after filtering out the background noise of CTL signal. [ABSTRACT FROM AUTHOR]

• The CTL sensor instrument could response to ethyl ether under 180 °C, which was lower than most of the reported CTL reaction temperatures. • The linear detection range was wide, ranging from 10 ppm to 5800 ppm (R = 0.9978, n = 7), and the detection limit was also low (4.3 ppm). • The CTL sensor showed the response time of 4 s and recovery time of 8 s, which was relatively short. • The pattern recognition results showed the analytes could be classified clearly. The low reaction temperature, excellent sensitivity, selectivity, stability and recognition performance indicated this CTL sensor was ideal for gas contaminants detection in confined spaces for the Internet of Things. Gaseous cataluminescence (CTL) sensor instrument was developed for detecting and measuring pernicious gases such as ethyl ether, acetone, n-hexane, chloroform by using aluminum/iron oxides composites. The materials synthesis, apparatus and software, optimal conditions (flow rate, wavelength, temperature and concentration), selectivity and stability were thoroughly studied. The results indicated the CTL sensor instrument could response to ethyl ether under 180 °C, which was lower than most of the reported CTL reaction temperatures. In addition, the results showed that the linear detection range was wide, ranging from 10 ppm to 5800 ppm (R = 0.9978, n = 7), and the detection limit was also low (4.3 ppm). Moreover, for ethyl ether detection, the CTL sensor showed the response time of 4 s and recovery time of 8 s, which was relatively short. The pattern recognition methods included PCA, KPCA were selected for evaluating the recognition performance of this CTL sensor, results showed the analytes could be classified clearly. The low reaction temperature, excellent sensitivity, selectivity, stability and recognition performance indicated this CTL sensor was ideal for gas contaminants detection in confined spaces for the Internet of Things. [ABSTRACT FROM AUTHOR]